There's a new JDBC driver that provides standard access to Apache Kafka via JDBC API. The current version connects to the KSQL engine to perform queries to Kafka and then, the engine translates those requests to Kafka requests.

KSQL is still a developer preview, and it has been designed to make it easier to read, write, and process streaming data in real-time, at scale, using SQL-like semantics. The developers say using SQL is an easy way to express stream processing transformations as an alternative to writing an application in a programming language such as Java or Python.

KSQL supports stream processing operations including aggregations, joins, windowing, and session management. KSQL doesn't let you do lookips on data; instead, it is used for continuous transformations. The example given by the developers is that of a stream of clicks from users along with a table of account information about those users being continuously updated. KSQL lets you model this stream of clicks, and table of users, and join the two together, even though the stream of clicks isn't a specific size.

The queries created using KSQL are described as continuous queries, transformations that run continuously as new data passes through them, on streams of data in Kafka topics.

The developers suggest it could be used in applications where you need to transform an input stream into an output stream, but the application is simple enough to make the SQL interface enough without the need to use Kafka’s native streams API. KSQL uses Kafka’s Streams API internally and they share the same core abstractions for stream processing on Kafka.

Streams can be created from a Kafka topic or derived from existing streams and tables.

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